Data sifting to finetune nanometer structures by the trillions

René Raaijmakers
Leestijd: 9 minuten

If headlines are any clue, machine learning is taking the semicon industry by storm. Bits&Chips talks to two of ASML’s data scientists about the impact their discipline has on the hardcore physics company. The litho giant is increasing its use of machine learning to support its holistic lithography products.

If you want to see data sciences walking hand in hand with physics, visit the data science groups at ASML. This workplace is crowded by scientists – most of them physicists – focused on finetuning lithography processes by sifting through mountains of data.

ASML may be known as an optics and mechanics stronghold but lithography actually never was a domain of pure physics alone. Even the first wafer stepper that was built at Philips’ laboratories in the early seventies needed external data to keep itself on the right track. Herman van Heek, the system architect of this machine, consulted the Dutch national meteorology service, KNMI, to check the air pressure on an hourly basis. This way, he prevented his machine from drifting during different weather conditions because of small changes in atmospheric pressure impacting the wavelength of the laser used in the interferometry system that positioned the wafer stage.

This article is exclusively available to premium members of Bits&Chips. Already a premium member? Please log in. Not yet a premium member? Become one and enjoy all the benefits.


Related content